Requests coming into contact centers today may take many forms beyond calls on traditional voice channels. Interactions with customers using channels like email, chat, and social media are increasing in frequency and number. New challenges are posed as the channels often contain long dialogs of information that represent a core dump of information. The core dump may be presented in a confusing and unclear jumble of statements. Furthermore, there may be several dialog turns back and forth between an agent, the customer, and others who may weigh in on a problem. There is no guarantee of order, validity, structure, or relevance of the information contained in these interactions. Because of the free form nature of the interactions, a burden falls on the agent or a supervisor to make sense of a conversation flow every time the agent works on a new work item.
Typically, contact center agents and supervisors read previous dialogs to understand the back and forth communications between parties. The agent and the supervisor may use timestamps (e.g., hours, days), keys, and other indicators to understand a timeline of events. Key phrases might include time keywords like “before this,” “after that,” and “then we did,” “before that I noticed” and other indicators that serve as relative time references. Manually parsing all of the information can be time consuming and much of the information may be irrelevant. When the agent is required to manually parse and summarize data from the dialogs, time and efficiency are lost. Additionally, manual parsing and summarizing may lead to customer dissatisfaction as it forces the customer to wait while a new agent and/or supervisor gets up to speed on the problem in real time.